8 most important customer problems that Conversational Voice AI is solving 💪
Voice AI has come a long way. In this article, we explore what customer problems it can realistically solve today and which ones will be solved in the next couple of years.
“Business Pain” represents how important the problem is for the customer. The higher the pain, the more urgent it is for the customer to solve it.
“AI Readiness” represents the industry’s technological readiness to solve the pain
Let’s go over the pains one by one.
1) Conversation visibility
You have 100 sales reps (or call center agents) and they receive/place calls all the time trying to close deals or serve customers.
How do you know if they are doing a good job? Just a couple of years ago, this was quite difficult to do. These days, all you need to have is a Conversational Intelligence tool (aka Speech Analytics) and you will get full visibility into every conversation.
Every customer can be recorded, transcribed and summarized for you and the team. These tools are super convenient and there are plenty of them available in the market - Gong, Avoma, CallMiner, SalesLoft, etc.
AI Readiness: 10/10, Pain: 10/10
2) Scaling voice conversations
There are multiple roles where the person needs to receive or place calls and talk to another human being on the other side. Call center agents, sales and business development reps, recruiters, and others.
Maintaining and growing such teams is exceptionally difficult. Businesses need to recruit talent, and then they need to onboard and retain them.
This is an expensive endeavor. No doubt, AI Voice Bots are going to take over and automate some of these functions. This revolution has already started and will only accelerate.
Poly.ai has some deployments of such technologies. Several startups (Air AI, SynthFlow) have demoed such capability but as far as I know, they haven’t deployed it in real-life scenarios yet.
AI Readiness: 5/10, Pain: 10/10
3) Language barrier
The ability to communicate verbally in an effective way is a foundational capability of any team and business. The language barrier has always been one of the top problems for humanity. It takes years for people to learn to speak in a non-native language. The pain is real and any business that has this pain would pay a lot of money to eliminate it.
Imagine there being a real-time speech-to-speech translation AI that people could use for communication over Zoom, Teams or Krisp. This would be a game-changer.
As far as I know, there are no real-life deployments of such technology yet.
AI Readiness: 3/10, Pain: 10/10
4) Taking meeting notes
In many companies, there are people dedicated to taking notes in meetings. For many years this has been a manual task that can be automated with Voice AI now.
Many tools already offer meeting transcription, summary, and follow-up generation.
The quality varies from 60%-80% for now. No doubt it will keep improving and the manual work will be fully automated in the coming year or two.
There are already multiple companies doing this:
AI Readiness: 7/10, Pain: 8/10
5) Onboarding and training of associates
Call center agent turnover rate is between 30%-45%. This means that a huge number of agents leave every year and managers need to find replacements and onboard/train them. This is a costly process and any automation/simplification of the process has a clear ROI.
Similarly, companies that need to hire a high number of SDRs or AEs, need to onboard and train them, otherwise, their sales conversion rates would decrease. Again, high-ROI endeavor.
Imagine a bot sitting on an agent’s machine that listens to the customer conversation and gives real-time hints that have a history of better conversion rates or customer satisfaction. The agent ramps up quicker due to this technology.
This technology already exists and is called AI Live Assist. Multiple companies already have shipped products with such technology:
AI Readiness: 7/10, Pain: 7/10
6) Accent barrier
As with the language barrier, human accent is a serious barrier that impacts understanding and comprehension of business conversations. Nearly all humans have accents when speaking in non-native languages and it’s extremely difficult to retrain them.
Call centers have special training programs for their agents to reduce accent. The cognitive load and stress on agents for such tasks are intense.
Imagine a Voice AI technology that would, in real-time, localize the speaker’s accent to the listener’s accent to improve understanding and comprehension.
Companies such as Krisp and Sanas are already deploying such technology in the call center industry.
AI Readiness: 6/10, Pain: 7/10
7) Background noises & voices
The problem of background noises and voices in calls has been around for more than 30 years. It creates a distraction for the call participants and prevents them from focusing on the core conversation. Background noise also creates a constant stress for the speakers.
In call centers, background noise can result in a customer satisfaction drop, longer conversations and mental stress for agents.
Luckily, AI-powered Noise Cancellation technology can fully solve this problem. Krisp has pioneered this technology in the industry and has large-scale deployments of it. It solves both the problem of noises as well as background voices. Zoom, MS teams and other applications also have invested in such technologies.
AI Readiness: 10/10, Pain: 6/10
8) Off-brand voice
Businesses always value on-brand communication with customers. Products like Grammarly provide such capability for written communication. The same could be done for voice communication as well.
Multiple Voice AI companies provide a variety of AI voices and then allow you to transform the speaker’s voice in real time. This means that potentially businesses could choose to apply these voice masks to their call centers or give this option to their agents.
It seems that the technology is mature enough however I’m not aware of such real-life deployments yet.
AI Readiness: 7/10, Pain: 3/10